Fast R-CNN - Explained!

In this video, we take a look the Fast RCNN network. What is it? Why is it better than the original RCNN? How do we train and make inference for object detection? ABOUT ME ⭕ Subscribe: https://www.youtube.com/c/CodeEmporiu... 📚 Medium Blog:   / dataemporium   💻 Github: https://github.com/ajhalthor 👔 LinkedIn:   / ajay-halthor-477974bb   RESOURCES [1 📚] Slides used in the video: https://link.excalidraw.com/p/readonl... [2 📚] Main paper of the video: https://arxiv.org/pdf/1409.1556 [3 📚] Code for VGG network: https://github.com/ajhalthor/computer... [4 📚] ILSVRC Image net competition in 2014 models ranked: https://image-net.org/challenges/LSVR... [1 📚] Main paper: https://arxiv.org/pdf/1504.08083 [2 📚] Slides used in the video: https://link.excalidraw.com/p/readonl... [3 📚] Architecture diagrams for VGG and Fast R-CNN. I also provide the raw drawio files that you can upload to [draw.io](http://draw.io) to plug and play: https://github.com/ajhalthor/computer... [4 📚] Smooth L1 loss used to compute localization loss: https://docs.pytorch.org/docs/stable/... [5 📚] Video explaining the original R-CNN. This is nice to watch before this video to get more context:    • R-CNN - Explained!   [6 📚] Paper that introduces spatial pyramid pooling. This is useful for addressing issues of scale invariance in Fast R-CNNs. I didn’t talk too much about this in the video to avoid confusion: https://arxiv.org/pdf/1406.4729 PLAYLISTS FROM MY CHANNEL ⭕ Reinforcement Learning:    • Reinforcement Learning 101   Natural Language Processing:    • Natural Language Processing 101   ⭕ Transformers from Scratch:    • Natural Language Processing 101   ⭕ ChatGPT Playlist:    • ChatGPT   ⭕ Convolutional Neural Networks:    • Convolution Neural Networks   ⭕ The Math You Should Know :    • The Math You Should Know   ⭕ Probability Theory for Machine Learning:    • Probability Theory for Machine Learning   ⭕ Coding Machine Learning:    • Code Machine Learning   MATH COURSES (7 day free trial) 📕 Mathematics for Machine Learning: https://imp.i384100.net/MathML 📕 Calculus: https://imp.i384100.net/Calculus 📕 Statistics for Data Science: https://imp.i384100.net/AdvancedStati... 📕 Bayesian Statistics: https://imp.i384100.net/BayesianStati... 📕 Linear Algebra: https://imp.i384100.net/LinearAlgebra 📕 Probability: https://imp.i384100.net/Probability OTHER RELATED COURSES (7 day free trial) 📕 ⭐ Deep Learning Specialization: https://imp.i384100.net/Deep-Learning 📕 Python for Everybody: https://imp.i384100.net/python 📕 MLOps Course: https://imp.i384100.net/MLOps 📕 Natural Language Processing (NLP): https://imp.i384100.net/NLP 📕 Machine Learning in Production: https://imp.i384100.net/MLProduction 📕 Data Science Specialization: https://imp.i384100.net/DataScience 📕 Tensorflow: https://imp.i384100.net/Tensorflow CHAPTERS 00:00 What is R-CNN? 02:40 What is wrong with R-CNN? 06:17 Structure of Fast R-CNN 11:42 RoI Pooling Explained 14:27 Training Fast R-CNN 28:31 Inference on Fast R-CNN 31:22 How Fast R-CNN solved each problem of R-CNN 33:00 Quiz Time 34:00 Summary